Most machinery operates by performing a predetermined set of events, which may also be referred to as tasks, in an ordered sequence to provide a process outcome. These events are precisely sequenced and timed according to the design intent of the process being performed by the machinery. These timed events may be initiated, controlled, monitored and/or measured by one or more computational devices, which may include controllers such as programmable logic controllers and/or programmable automation controllers, or the like.
As the process is performed, the duration of a timed event may vary from one process cycle to another as the process conditions change, which may vary the duration of the process cycle, the throughput and/or efficiency of the machinery, and/or the process outcome. Variation in the duration of a timed event may indicate a process condition trending toward a downtime condition, such as a tool or equipment failure, a process condition requiring maintenance to prevent productivity loss, a potential quality issue, or other condition affecting the process outcome. Known predictive methods of monitoring machinery and/or automated processes, such as machinery vibration analysis, may not sufficiently discriminate sources of variation to effectively predict process conditions which may require intervention to prevent downtime, productivity loss, or quality issues.